# Reddit Search Scraper Pro (`prince.sh/reddit-search-scraper`) Actor Search Reddit for posts and comments by keyword. Get titles, body, upvotes, comment threads, flair, and metadata. Filter by sort order, time range, and minimum upvotes. Perfect for sentiment analysis, AI training data, brand monitoring, and trend research. - **URL**: https://apify.com/prince.sh/reddit-search-scraper.md - **Developed by:** [Prince Jain](https://apify.com/prince.sh) (community) - **Categories:** Social media, AI, News - **Stats:** 2 total users, 1 monthly users, 83.3% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $0.0015 / post This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## Reddit Search Scraper Pro Search Reddit posts and comments by keyword via JSON API. Export subreddit, score, flair, and comment threads for sentiment analysis, brand monitoring, and AI training. **Pricing:** $1.50 per 1,000 posts · $0.50 per 1,000 comments (pay-per-event, no monthly subscription). Built by [Prince Jain](https://w.prince.sh/website) · [mail@prince.sh](mailto:mail@prince.sh) ### What does this Actor do? Reddit Search Scraper Pro extracts structured data from the web and saves it to a dataset you can download as JSON, CSV, or Excel. It runs on the Apify platform with pay-per-event pricing — you only pay for results you receive. ### Use cases - Brand monitoring and sentiment analysis across Reddit - Collect structured post and comment data for LLM fine-tuning - Track keyword trends across subreddits with sort and time filters ### Input Configure the run in the Apify Console or via API. See the **Input** tab for all fields and prefill examples. Optional: add a **Proxy configuration** for sites that require residential IPs. ### Output fields Each result includes: `title`, `selftext`, `author`, `subreddit`, `score`, `numComments`, `flair`, `permalink`. View results in the run's **Dataset** tab or fetch them via the Apify API. ### Pricing | Event | Price | |-------|-------| | Actor start | $0.00005 | | Result | See store pricing tab | $1.50 per 1,000 posts · $0.50 per 1,000 comments. No platform usage fees with pay-per-event on Apify Store. ### FAQ **Do I need an API key?** No — this Actor uses public endpoints and does not require third-party API credentials. **Can I schedule runs?** Yes. Use Apify Schedules to run this Actor hourly, daily, or on a custom cron. **How do I integrate with my workflow?** Call the Actor via the Apify API, webhooks, or MCP. Results land in an Apify dataset. ### Keywords Reddit scraper, Reddit search API, subreddit data export, social media monitoring, AI training data ### Author **Prince Jain** — [https://w.prince.sh/website](https://w.prince.sh/website) · [mail@prince.sh](mailto:mail@prince.sh) Apify Store: `prince.sh/reddit-search-scraper` # Actor input Schema ## `searchQueries` (type: `array`): Keywords to search Reddit for. ## `maxResults` (type: `integer`): Maximum number of posts to scrape per search query. ## `sort` (type: `string`): Select sort option. ## `timeFilter` (type: `string`): Select timeFilter option. ## `minUpvotes` (type: `integer`): Only return posts with at least this many upvotes. ## `includeComments` (type: `boolean`): If true, fetch top comments from each post. ## `maxCommentsPerPost` (type: `integer`): Max comments per post. ## `proxyConfiguration` (type: `object`): Optional Apify proxy (recommended for anti-bot sites like Trustpilot, Etsy, Glassdoor). ## Actor input object example ```json { "searchQueries": [ "AI jobs", "OpenAI" ], "maxResults": 100, "sort": "relevance", "timeFilter": "all", "minUpvotes": 0, "includeComments": false, "maxCommentsPerPost": 20, "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } } ```` # Actor output Schema # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "searchQueries": [ "AI jobs", "OpenAI" ], "maxResults": 100, "maxCommentsPerPost": 20, "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } }; // Run the Actor and wait for it to finish const run = await client.actor("prince.sh/reddit-search-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "searchQueries": [ "AI jobs", "OpenAI", ], "maxResults": 100, "maxCommentsPerPost": 20, "proxyConfiguration": { "useApifyProxy": True, "apifyProxyGroups": ["RESIDENTIAL"], }, } # Run the Actor and wait for it to finish run = client.actor("prince.sh/reddit-search-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "searchQueries": [ "AI jobs", "OpenAI" ], "maxResults": 100, "maxCommentsPerPost": 20, "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } }' | apify call prince.sh/reddit-search-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=prince.sh/reddit-search-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Reddit Search Scraper Pro", "description": "Search Reddit for posts and comments by keyword. Get titles, body, upvotes, comment threads, flair, and metadata. Filter by sort order, time range, and minimum upvotes. Perfect for sentiment analysis, AI training data, brand monitoring, and trend research.", "version": "0.1", "x-build-id": "zxJaNmTwCZUWHvDFv" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/prince.sh~reddit-search-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-prince.sh-reddit-search-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/prince.sh~reddit-search-scraper/runs": { "post": { "operationId": "runs-sync-prince.sh-reddit-search-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/prince.sh~reddit-search-scraper/run-sync": { "post": { "operationId": "run-sync-prince.sh-reddit-search-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "required": [ "searchQueries", "maxResults" ], "properties": { "searchQueries": { "title": "Search queries", "type": "array", "description": "Keywords to search Reddit for.", "items": { "type": "string" } }, "maxResults": { "title": "Max results per query", "minimum": 1, "maximum": 1000, "type": "integer", "description": "Maximum number of posts to scrape per search query.", "default": 100 }, "sort": { "title": "Sort by", "enum": [ "relevance", "hot", "top", "new", "comments" ], "type": "string", "description": "Select sort option.", "default": "relevance" }, "timeFilter": { "title": "Time filter", "enum": [ "hour", "day", "week", "month", "year", "all" ], "type": "string", "description": "Select timeFilter option.", "default": "all" }, "minUpvotes": { "title": "Min upvotes", "minimum": 0, "type": "integer", "description": "Only return posts with at least this many upvotes.", "default": 0 }, "includeComments": { "title": "Include comments", "type": "boolean", "description": "If true, fetch top comments from each post.", "default": false }, "maxCommentsPerPost": { "title": "Max comments per post", "minimum": 1, "maximum": 500, "type": "integer", "description": "Max comments per post.", "default": 20 }, "proxyConfiguration": { "title": "Proxy configuration", "type": "object", "description": "Optional Apify proxy (recommended for anti-bot sites like Trustpilot, Etsy, Glassdoor)." } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```